Particularly for small trials, the P value from a Fisher's exact test can be discrepant from a Chi squared test. 1 Other methods, such as a Chi squared test, are commonly used to compare a dichotomous (binary) outcome in clinical trials. Ridgeon 2016 3: Included 56 critical care RCTs with an endpoint of mortalityīy definition, the fragility index is calculated using a Fisher's exact test.Evaniew 2015 2: Included 40 orthopedic spine surgery RCTs with a variety of different endpoints.Walsch 2014 1: Included 399 randomized controlled trials (RCTs) from five high-impact journals.When loss to follow-up was reported, 52.9% of trials had a larger fragility index compared to the number of patients lost to follow-upĪt least two other publications have summarized the fragility index within other areas of medicine:.10% of trials had a fragility index of zero (see Fragility Index of Zero for an explanation).25% of trials had a fragility index ≤ 3.The median fragility index was 8 (IQR 3 to 18).1 This study found the following results, which serves to describe the landscape of fragility index among clinical trials that in general are considered high-quality or "robust" studies: In the manuscript introducing the concept, a convenience sample of 399 randomized controlled trials with statistically significant results were analyzed from five high-impact journals. There is no specific fragility index that is accepted as being a "good" (robust) or "bad" (fragile) value. In essence, the calculation describes how many patients would have had to have a different outcome (within the group with the fewest number of events) to make a study's results not statistically significant. The fragility index is calculated by converting one patient in the group (control or experimental group) from a "non-event" to an "event" outcome and recalculating a two-sided Fisher's exact test until the P value meets or exceeds 0.05. The intent of the fragility index is to be used in conjunction with the P value, 95% confidence interval, and various measures describing benefit or risk (relative risk reduction, absolute risk reduction, etc). The larger the fragility index the better (more robust) a trial's data are.
The fragility index is a number indicating how many patients would be required to convert a trial from being statistically significant to not significant (p ≥ 0.05). The fragility index is a measure of the robustness (or fragility) of the results of a clinical trial.